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Image enhancement and post-processing for low resolution compressed video

Image enhancement and post-processing for low resolution compressed video
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摘要 This research paper recommends the point spread function(PSF)forecasting technique based on the projection onto convex set(POCS)and regularization to acquire low resolution images.As the environment for the production of user created contents(UCC)videos(one of the contents on the Internet)becomes widespread,resolution reduction and image distortion occurs,failing to satisfy users who desire high quality images.Accordingly,this research neutralizes the coding artifact through POCS and regularization processes by:1)factoring the local characteristics of the image when it comes to the noise that results during the discrete cosine transform(DCT)and quantization process;and 2)removing the blocking and ring phenomena which are problems with the existing video compression.Moreover,this research forecasts the point spread function to obtain low resolution images using the above-mentioned methods.Thus,a method is suggested for minimizing the errors found among the forecasting interpolation pixels.Low-resolution image quality obtained through the experiment demonstrates that significant enhancement was made on the visual level compared to the original image. This research paper recommends the point spread function (PSF) forecasting technique based on the projection on-to convex set (POCS) and regularization to acquire low resolution images. As the environment for the production of user created contents (UCC) videos (one of the contents on the Internet) becomes widespread, resolution reduction and image distortion occurs, failing to satisfy users who desire high quality images. Accordingly, this research neutralizes the coding ar-tifact through POCS and regularization processes by: 1) factoring the local characteristics of the image when it comes to the noise that results during the discrete cosine transform (DCT) and quantization process; and 2) removing the blocking and ring phenomena which are problems with the existing video compression. Moreover, this research forecasts the point spread function to obtain low resolution images using the above-mentioned methods. Thus, a method is suggested for minimizing the errors found among the forecasting interpolation pixels. Low-resolution image quality obtained through the experiment dem-onstrates that significant enhancement was made on the visual level compared to the original image.
出处 《Journal of Measurement Science and Instrumentation》 CAS 2013年第1期30-33,共4页 测试科学与仪器(英文版)
基金 The MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2012-H0301-12-2006)
关键词 discrete cosine transform(DCT) projection onto convex set(POCS) image resolution discrete cosine transform (DCT) projection onto convex set (POCS) image resolution
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参考文献4

  • 1SHEN Mei-yin, Kuo C-C J. Review of postprocessing techniques for compression artifact removal. Journal of Visual Communication and Image Representation, 1998, 9(1): 2-14.
  • 2LI Zhen, Delp E J. Blocking artifact reduction using a transform-domain markov random field moel. IEEE Transactions on Circuits and Systems for Video Technolo- gy, 2005, 15(12): 1583-1593.
  • 3ZHAO Meng. Video enhancement using content-adaptive least mean square filter. PhD thesis. Eindhoven Universi- ty of Technology, 2006.
  • 4Chen H , Leou J J. A visual attention approach to im- age interpolation. In: Proceedings of IEEE International Conference on Multimedia and Expo, 2008: 169-172.

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